Write a function that mutates a tree by adding the level number to each label on the level, where the root node is on level 1.
def levels(tree):
>>> t = Tree(1, [Tree(4, [Tree(5)]), Tree(6)])
>>> levels(t)
Tree(2, [Tree(6, [Tree(8)]), Tree(8)])
>>> t
Tree(2, [Tree(6, [Tree(8)]), Tree(8)])

Write a function that will return a list of paths from leaf to root where the leaf value is equal to val. Each path should be represented as a linked list.
def paths(tree, val):
>>> t = Tree(1, [Tree(2, [Tree(3), Tree(5)]), Tree(7, [Tree(4, [Tree(3)])])])
>>> paths(t, 3)
[Link(3, Link(2, Link(1))), Link(3, Link(4, Link(7, Link(1))))]
    path_list= []
    def paths_helper(tree, path):
        if ________:
            ________
        else:
            ________
            ________
    paths_helper(____, ____)
    return path_list

Write out a function that will take in a list of unique values and create a binary search tree out of it.
def make_bst(lst):
>>> lst = [8, 5, 3, 9]
>>> make_bst(lst)
Tree(8, [Tree(5, [Tree(3)]), Tree(9)])
    if ______:
        return
    label = ______
    if ______:
        return ______
    less, greater = ____, ____
    for ______:
        if ______:
            ______
        else:
            ______
    left = ______
    right = ______
    return ______

Write out a function that will take in a sorted list of unique elements and create a balanced binary search tree out of it. You may want to define the given function, find_median_index to help you.
def make_balanced_bst(sorted_lst):
>>> lst = [1, 2, 3, 4, 5, 6, 7]
>>> make_balanced_bst(lst)
Tree(4, [Tree(2, [Tree(1), Tree(3)]), Tree(6, [Tree(5), Tree(7)])])
    if ______:
        return
    else if ______:
        return ______
    median_index = find_median_index(______)
    label = ______
    left = ______
    right = ______
    return ______
def find_median_index(lst):
    return ______